code: def test_bert_tokenizer_all_meta(caplog):
      caplog.set_level(logging.CRITICAL)
  
      lang_model = "bert-base-cased"
  
      tokenizer = Tokenizer.load(
          pretrained_model_name_or_path=lang_model, do_lower_case=False
      )
  
      basic_text = "Some Text with neverseentokens plus !215?#. and a combined-token_with/chars"
  
      tokenized = tokenizer.tokenize(basic_text)
      assert tokenized == [
          "Some",
          "Text",
          "with",
          "never",
          "##see",
          "##nto",
          "##ken",
          "##s",
          "plus",
          "!",
          "215",
          "?",
          "#",
          ".",
          "and",
          "a",
          "combined",
          "-",
          "token",
          "_",
          "with",
          "/",
          "ch",
          "##ars",
      ]
  
      encoded_batch = tokenizer.encode_plus(basic_text)
      encoded = encoded_batch.encodings[0]
      words = np.array(encoded.words)
      words[words == None] = -1
      start_of_word_single = [False] + list(np.ediff1d(words) > 0)
      assert encoded.tokens == [
          "[CLS]",
          "Some",
          "Text",
          "with",
          "never",
          "##see",
          "##nto",
          "##ken",
          "##s",
          "plus",
          "!",
          "215",
          "?",
          "#",
          ".",
          "and",
          "a",
          "combined",
          "-",
          "token",
          "_",
          "with",
          "/",
          "ch",
          "##ars",
          "[SEP]",
      ]
      assert [x[0] for x in encoded.offsets] == [
          0,
          0,
          5,
          10,
          15,
          20,
          23,
          26,
          29,
          31,
          36,
          37,
          40,
          41,
          42,
          44,
          48,
          50,
          58,
          59,
          64,
          65,
          69,
          70,
          72,
          0,
      ]
      assert start_of_word_single == [
          False,
          True,
          True,
          True,
          True,
          False,
          False,
          False,
          False,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          True,
          False,
          False,
      ]
  
file_path: FARM/test/test_tokenization.py
imports: import logging
  import pytest
  import re
  from transformers import BertTokenizer, BertTokenizerFast, RobertaTokenizer, RobertaTokenizerFast, XLNetTokenizer, XLNetTokenizerFast, ElectraTokenizerFast
  from tokenizers.pre_tokenizers import WhitespaceSplit
  from farm.modeling.tokenization import Tokenizer, tokenize_with_metadata, truncate_sequences
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: test_bert_tokenizer_all_meta(caplog) without return types